Amazon is a well-known name to all of us. It is among the leading e-Commerce platforms. Apart from offering online shopping, Amazon serves us with its different services like Amazon Pay, Amazon Pantry, Amazon Web Services (AWS), and many more. For a company like Amazon, the amount of data collected on a regular basis is very big. To manage such large amounts of data companies leverage big data technology.
For any company, one of the most valuable assets is its customer base because it is the customer who turns a company into a brand, and if a company fails to meet the expectations of its customers, that probably leads to its decline.
Big data is a technology that helps in the management of large amounts of data. In today’s times when almost everything has become digital, data collection is also being digitized. Data for a company refers to every crucial information the company possesses about its customers, market insights, and even its competitors’ marketing strategies. All these data are analyzed and worked upon to form strategies accordingly.
Amazon leverages its data via its recommendation engine. Everytime a user searches for a specific product, this data helps the platform to guess what else the user can have interest in. This in turn allows Amazon to enhance their procedure of convincing the consumer into purchasing it.
Amazon collects individual data regarding each of its customers as they make use of the website. Additionally to what the customer purchases, Amazon also keeps track of what items were viewed, the shipping address of the users and the reviews left by the user. Big Data has greatly played a role in making Amazon a leading e-commerce platform. The inventory is tracked through the manufacturers for ensuring that the orders are executed fast. Big Data enables the warehouse nearest to the user to be chosen, reducing the shipping expenses considerably.
So, in this blog, we will discuss the use of Big Data in Amazon. We will look at the ways it is doing it. At first, we should briefly recall big data analytics.
What is Big Data Analytics?
Big Data is a term that is applied to datasets whose size or type is way complex than traditional data sets and is beyond the ability of traditional relational databases to capture, manage, and process with efficiency. Nowadays, since the introduction of new technologies like Artificial Intelligence, the Internet of Things, mobile applications, and the web, the amount and complexity of data has increased.
Now, talking about Big Data Analytics, it means to analyze diverse and large data sets that are structured, semi-structured, and unstructured with the help of advanced analytics techniques. Analysis of big data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable.
Now, having understood the relevant terms, we should move to the main part of the blog i.e. how Amazon uses big data analytics?
5 Ways in which Amazon Uses Big Data for Monitoring
Amazon is a leader in collecting, storing, processing and analyzing personal information from every customer as a means of determining how customers are spending their money. The company uses predictive analytics for targeted marketing which helps them in increasing customer satisfaction and get loyalty in return. Let’s have a look at how they do it?
Alexa Voice Recordings
Amazon offers virtual assistants such as Echo and Echo Show, which include a camera as well as speakers. We use it for several purposes like getting weather updates, daily news, or ordering shampoo and these are all a voice command away.
However, we may not realize that these audio recordings are being uploaded to Amazon’s servers. The company says that these voice files help make the Alexa experience better. It helps by enabling better speech recognition from a diverse group of customers and hence accurate message processing as well as functioning.
Amazon’s Alexa- a smart home solution
However, for some customers, this may be a privacy concern. For such customers, who are not comfortable with their voice recordings being stored in the cloud, they can delete them one by one or by data range, using the Alexa enabled assistant.
Personalized Recommendation System
Amazon is a leader in using a comprehensive, collaborative filtering engine (CFE). The company follows the concept of behavioral analytics. It analyzes the purchasing patterns of the customers from the previously purchased items, items in the shopping cart or on their wishlist, the products reviewed and rated by them, to most searched products.
This information is then used to recommend additional products that other customers purchased when buying those same items. For example, if a customer adds a mobile phone to its shopping cart, mobile cases are recommended for purchase.
In this way, Amazon’s big data uses the power of suggestion to encourage impulsive purchases from a customer and further enhance the whole shopping experience. This seems to pretty much work for the company as it generates 35% of its annual sales using this method.
Since there is so much competition out there, Big data shows that a customer starts looking for alternatives if there is a delay in the delivery period. This compelled Amazon to come up with something like One-Click ordering. One-Click ordering is a patented feature that is automatically enabled when a person places its first order and enters a shipping address and a payment method. If someone chooses One-Click ordering, he/she has 30 minutes to decide on the purchase. After that, the product is automatically charged via the added payment method and shipped to the added address.
Anticipatory Shipping Model
Amazon's licensed anticipatory delivery model additionally utilizes large information for anticipating the items a customer is probably going to buy, when he/she may get them, and where he/she may require the items. The things are shipped off a neighborhood circulation focus or stockroom so they will be prepared for transportation once the customer requests them.
Amazon utilizes prescient examination to expand its item deals and net revenues while diminishing its conveyance time and general expenses.
Book Recommendations from Kindle Highlighting
After acquiring Goodreads in 2013, Amazon integrated the social networking service of roughly 25 million users with some Kindle functions. This enabled the users to highlight words and notes and also to share them among their peers as a means to discuss the book. The company benefited from this in a way that it could regularly monitor the highlighted words in Kindle to know about the interest of the readers. They further used this data to recommend ebooks to their customers and also to enhance the reading experience.
So, these were the ways in which Amazon uses big data to monitor us. Now, we will look at some ways they implement it.
Referred blog: Big Data Applications
“In retail, while things like the size of the catalogue, advertising and other stuff might play a role in success, at Amazon, I think success is largely technology driven,”
- Werner Vogels, Chief Technology Officer, Amazon
How Amazon implements big data?
After collecting crucial information about the consumers, Amazon uses those insights to better serve them. Let’s see how?
Supply Chain Optimization
When it comes to increasing efficiency, Supply Chain Optimization is the best way to achieve it. Amazon wants to fulfill the orders quickly and to achieve this feat the company connects with the manufacturers and tracks their inventories. Amazon’s big data analyzes the available data and locates the closest warehouse to a customer/vendor to reduce the shipping costs. Additionally, graph theory helps in deciding the best delivery schedule, route, and product groupings which further reduces the shipping expenses.
Recommended blog - Supply Chain Management
Big Data is also used to manage the prices of products to attract more customers and eventually increase the net profit. Before Big Data was used in price optimization, products’ prices remained unchanged irrespective of the frequency on the website. Now, prices change frequently. One of the reasons is because big data platforms assess a person’s willingness to buy.
Prices are set according to your activity on the website, competitors’ pricing, product availability, item preferences, order history, expected profit margin, and other factors. Product prices generally change every 10 minutes as big data is updated and analyzed. As a result, Amazon typically offers discounts on best-selling items and earns larger profits on less popular items. This benefited the company in increasing their annual income by 143% from 2016 to 2019, according to a report.
To screen purchases and return requests for signs of fraud
Being a leader in the e-commerce market, there remains a risk of retail fraud with the company. To avoid this, the company collects thousands of historical and real-time data points on every order and uses machine learning algorithms to find transactions with an elevated likelihood of being fraudulent.
Because of Amazon's proactive methodology, and huge information calculations changed to address exact issues, the organization can likewise examine dubious bring requests back.
For instance, if enormous information shows an individual has returned a bizarrely high amount of products in the course of recent months, the organization may explore further. In 2018, some long-term clients announced getting restricted for making what Amazon esteemed an excessive number of returns.
To encourage people to buy more with each order
Amazon’s product recommendations are the most familiar application of big data to its users and, as it is mentioned above, they also use it to collect insights. Later, it is made to work by presenting users with related items based on things already in their carts and previously purchased products.
Personalized shopping experience on Amazon
With the arrival of Amazon Personalize, the organization facilitated developers with a simple-to-utilize and profoundly versatile stage that offers proposals to clients across almost any area. Different organizations could take advantage of Amazon's innovation for their clients, giving them stock choices going from garments, food and that's only the tip of the iceberg.
At the point when Amazon can effectively engage clients with customized picks and make them need to spend more, organization benefits rise and individuals get the recognition that Amazon is where they can purchase basically anything they may require.
To change and modify physical stores
Amazon Go, the brand's cashier-less accommodation store brand, likewise vigorously depends on information to work. Sensors identify which things individuals get to purchase, and cameras guarantee customers don't prevail with shoplifting endeavors. Despite the fact that the organization has not really expounded on the information it gathers about Amazon Go customers and why, it's feasible the firm would utilize the information to improve its stores.
Recommended blog - Hive Big Data
For instance, if cameras indicated individuals with child buggies experienced difficulty exploring the walkways, Amazon may make them more extensive. Then again, if deals that demonstrated vegetarian amicable things sell particularly quickly in a particular locale, it may arrange a greater amount of those items to coordinate client needs.
So, these were the ways in which Amazon is collecting and implementing big data to drive more customer traffic. The process of data collection starts right from the moment a person navigates the website. Nowadays, we can see it happening so often. We search for a product on the platform and its ads start to come before us at every possible place.
Technology is changing the dynamics of everything and businesses are no exception. Amazon is a giant in the e-commerce platform and now we know the reason, wise use of technology.